Efficientvit: Memory efficient vision transformer with cascaded group attention
Vision transformers have shown great success due to their high model capabilities.
However, their remarkable performance is accompanied by heavy computation costs, which …
However, their remarkable performance is accompanied by heavy computation costs, which …
[HTML][HTML] Workflow performance prediction based on graph structure aware deep attention neural network
With the rapid growth of cloud computing, efficient operational optimization and resource
scheduling of complex cloud business processes rely on real-time and accurate …
scheduling of complex cloud business processes rely on real-time and accurate …
[HTML][HTML] Towards Efficient Resource Allocation for Federated Learning in Virtualized Managed Environments
F Nikolaidis, M Symeonides, D Trihinas - Future Internet, 2023 - mdpi.com
Federated learning (FL) is a transformative approach to Machine Learning that enables the
training of a shared model without transferring private data to a central location. This …
training of a shared model without transferring private data to a central location. This …
Intelligent horizontal autoscaling in edge computing using a double tower neural network
Edge computing is characterized by varying workload intensities that have a strong effect on
applications' performance and requirements in terms of resources. Thus, in order to maintain …
applications' performance and requirements in terms of resources. Thus, in order to maintain …
A two-stage multi-objective task scheduling framework based on invasive tumor growth optimization algorithm for cloud computing
Q Hu, X Wu, S Dong - Journal of Grid Computing, 2023 - Springer
Task scheduling in cloud computing is usually required to achieve multiple goals from the
perspective of cloud service providers, users, environmental benefits, and so on. However …
perspective of cloud service providers, users, environmental benefits, and so on. However …
DeGTeC: a deep graph-temporal clustering framework for data-parallel job characterization in data centers
Y Liang, K Chen, L Yi, X Su, X Jin - Future Generation Computer Systems, 2023 - Elsevier
Complex data-parallel job contains task dependency information defined as Directed Acyclic
Graph (DAG). For convenience, the DAG presented data-parallel jobs are named as DAG …
Graph (DAG). For convenience, the DAG presented data-parallel jobs are named as DAG …
Zero overhead monitoring for cloud-native infrastructure using {RDMA}
Cloud services have recently undergone a major shift from monolithic designs to
microservices running on the cloud-native infrastructure, where monitoring systems are …
microservices running on the cloud-native infrastructure, where monitoring systems are …
Bursting oscillations and bifurcation mechanism in a fully integrated piecewise-smooth chaotic system
This paper aims to show and investigate bursting oscillator and bifurcation phenomena in a
piecewise-smooth memristor-based Shimizu–Morioka (SM) system. First, a piecewise …
piecewise-smooth memristor-based Shimizu–Morioka (SM) system. First, a piecewise …
: Monitoring Large-Scale Cloud-Native Infrastructure Using One-Sided RDMA
Cloud services have shifted from monolithic designs to microservices running on cloud-
native infrastructure with monitoring systems to ensure service level agreements (SLAs) …
native infrastructure with monitoring systems to ensure service level agreements (SLAs) …
Batch Jobs Load Balancing Scheduling in Cloud Computing Using Distributional Reinforcement Learning
T Li, S Ying, Y Zhao, J Shang - IEEE Transactions on Parallel …, 2023 - ieeexplore.ieee.org
In cloud computing, how to reasonably allocate computing resources for batch jobs to
ensure the load balance of dynamic clusters and meet user requests is an important and …
ensure the load balance of dynamic clusters and meet user requests is an important and …